• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.10-17
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• 2013

This thesis proposes an automatic embedded core generator system that supports branch prediction. The proposed system includes a dynamic branch prediction module that enhances execution speed of target applications by inserting history/direction flags into BTAC(Branch Target Address Cache). Entries of BHT(Branch History Table) and BTAC are determined based on branch informations extracted by simulation. To verify the effectiveness of the proposed branch prediction module, ARM9TDMI core including a dynamic branch predictor was described in SMDL and generated. Experimental results show that as the number of entry rises, area increase up to 60% while application execution cycle and BTAC miss rate drop by an average of 1.7% and 9.6%, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1046-1055
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• 1994

In this paper, to design high speed 1 line VRAM(Video RAM) suitable for image signal processing with ASIC(Application Specific IC) method, the VRAM memory core has been designed using 3-TR dual-port dynamic cell which has excellent access time and integration characteristics. High speed pipeline operation was attained by separating the first row from the subarray 1 memory core and the simultaneous I/Q operation for a selected single address was made possible by adopting data-latch scheme. Peripheral circuits were designed implementing address selector and 1/2V voltage generator. Integrated ASIC has been optimized using 1.5[ m] CMOS design rule.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.804-806
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are new iy defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2134-2153
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• 2013

A network-coding-based scheme is proposed to improve the energy efficiency of distributed storage systems in WSNs (Wireless Sensor Networks). We mainly focus on two problems: firstly, consideration is given to effective distributed storage technology; secondly, we address how to effectively repair the data in failed storage nodes. For the first problem, we propose a method to obtain a sparse generator matrix to construct network codes, and this sparse generator matrix is proven to be the sparsest. Benefiting from this matrix, the energy consumption required to implement distributed storage is reduced. For the second problem, we designed a network-coding-based iterative repair method, which adequately utilizes the idea of re-encoding at intermediate nodes from network coding theory. Benefiting from the re-encoding, the energy consumption required by data repair is significantly reduced. Moreover, we provide an explicit lower bound of field size required by this scheme, which implies that it can work over a small field and the required computation overhead is very low. The simulation result verifies that the proposed scheme not only reduces the total energy consumption required to implement distributed storage system in WSNs, but also balances energy consumption of the networks.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.861-868
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• 2017

In this study, a novel magnetic field generator, using a shielding effect for controlling the dynamic stiffness and damping of magnetorheological gels, is proposed. A magnetorheological gel is a smart material that can alter its stiffness and damping, and it can be used as a vibration absorber and in vehicle suspension. It is necessary to control the magnetic field to use magnetorheological gels in various applications. There are two types of magnet field generators, namely the electromagnet and permanent magnet, and the electromagnet is generally used in practical applications. However, owing to its limitations, the electromagnet is not suitable for long-term use. Therefore, in this paper, a novel magnetic field generator is proposed to address such problems for use in real applications.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• The KIPS Transactions:PartC
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• v.10C no.2
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• pp.233-240
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• 2003

In this paper, an improved architecture of turbo codec for IMT-2000 is proposed. The encoder consists of an interleaver using an on-the-fly type address generator and a modified shift register instead of an external RAM, and the decoder uses a decreased number of RAM. The proposed architecture is simulated with C/VHDL languages, where BER (bit-error-rate) performances are generally in agreement with previous data by varying interaction numbers, interleaver block sizes and code rates.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.445-450
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• 2014

Jeju power system is connected to the mainland power system through HVDC, and receives about half of required electricity through the HVDC lines. Jeju power system already experienced black out when a generator tripped at the moment of the HVDC line faults. But, UFR operated as was expected when HVDC line fault occurred at that time. As the penetration level of wind turbines increases, it is required to set UFR again considering intermittent wind turbin outputs. In this paper, we address a new way of UFR setting through computer simulation.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.511-517
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• 2015

Determination of the required reserve capacity has an important function in operation of power system and it is calculated based on the largest loss of supply. However, conventional method cannot be applied in future power system, because potential grid-connected distributed generator and abnormal temperature cause the large load imbalance. Therefore this paper address new framework for determining the optimal required reserve capacity taking into account the real time load imbalance. At first, we introduce the way of operating reserve resources which are the secondary, tertiary, Direct Load Control (DLC) and Load shedding reserves to make up the load imbalance. Then, the formulated problem can be solved by the Probabilistic Dynamic Programming (PDP) method. In case study, we divide two cases for comparing the cost function between the conventional method and the proposed method.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.353-360
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• 2016

Series hybrid electric vehicles (SHEVs) having multiple power sources such as an engine- generator (EnGen), a battery, and an ultra-capacitor require a power control unit with high power density and reliable control operation. However, manufacturing using separate individual power converters has the disadvantage of low power density and requires a large number of power and signal cable wires. It is also difficult to implement the optimal power distribution and fault management algorithm because of the communication delay between the units. In order to address these concerns, this approach presents a design methodology and a power control algorithm of an integrated power converter for the SHEVs powered by multiple power sources. In this work, the design methodology of the integrated power control unit (IPCU) is firstly elaborately described, and then efficient and reliable power distribution algorithms are proposed. The design works are verified with product-level and vehicle-level performance experiments on a 10-ton SHEV.